st: RE: Efficient parallel computing in Stata/MP

[Daniel Feenberg <feenberg@nber.org>]

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Demian Panigo
> Sent: 27 September 2013 01:02
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Efficient parallel computing in Stata/MP
>
> Dear Statalist members: I need some help, because I'm not sure about
> some Stata/MP properties for parallel computing.
> We know from http://www.stata.com/statamp/statamp.pdf that many
> estimation commands (e.g. regress) are almost fully parallelizable and
> that average efficiency for all commands is around 72%. So, in
> standard linear regression problems (e.g running one million equations
> for parameter stability analysis), using Stata/MP in a multiple-core
> CPU would be an optimal time saving strategy.
> However, it is also possible to exploit the multi-core CPU environment
> by working with multiple parallel Stata/MP instances (e.g. using 4
> parallel Stata/MP instances to run 250.000 linear regressions with
> each core).
> My question is simple.... Can I save some time by using this "dual
> parallelism" methodology? (because parallel computing is
> authomatically used by Stata/MP to parallelize internal tasks of, for
> example, regress; and because I also parallelize the whole set of
> regressions between 4 cores, by means of multiple Stata/MP instances).
> Thanks in advance
> *
In my experience, Stata/MP fully exploits as many real cores as are 
available, very efficiently for regression commands. If you have 
hypercores, running multiple Stata jobs will exploit those efficiently 
also. I posted the results of a simple experiment at:
  http://www.nber.org/stata/efficient

under heading "Stata/MP".

-parallel.ado- is a very interesting routine. It will start up multiple 
Stata processes and let each one read a part of the dataset, then combine 
the results into a single dataset. For processes that are single-threaded 
for no good reason, or if you don't have Stata/MP, it seems like a great 
idea. I believe it will also work well with hyper-cores, but I have no 
experience with it. But for I/O it would just make things worse, since 
each thread has to read the entire dataset.
See

  http://www.stata.com/statamp/report.pdf

for a more discouraging report on hyper-cores. I don't have an explanation 
for the difference in experiences. There is no substitute for 
experimentation on your actual hardware, and there would be interest on 
this list in your experience.
Daniel Feenberg
NBER
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